Method to prepare virtual assay using gel permeation chromatography

ABSTRACT

Systems and methods are disclosed for providing virtual assays of an oil sample such as crude oil based on gel permeation chromatography (GPC) carried out on the oil sample or a solution of the oil sample in a GPC solvent, and the density of the oil sample. The virtual assay provides a full range of information about fractions of the oil sample including naphtha, gas oil, vacuum gas oil, vacuum residue, and other information about the properties of the oil sample. Using the system and method herein, the virtual assay data pertaining to these several fractions of the oil sample and the oil sample itself are obtained without fractionation of the oil sample into the several components.

RELATED APPLICATIONS

Not applicable.

BACKGROUND Field of the Invention

The present invention relates to methods and systems for evaluating an oil sample such as crude oil to provide a virtual assay.

Description of Related Art

Crude oil originates from the decomposition and transformation of aquatic, mainly marine, living organisms and/or land plants that became buried under successive layers of mud and silt some 15-500 million years ago. They are essentially very complex mixtures of many thousands of different hydrocarbons. In addition to crude oils varying from one geographical region to another and from field to field, it has also been observed that the properties of the crude oil from one field may change with time, as oil is withdrawn from different levels or areas of the field. Depending on the source and/or time of withdrawal, the oil predominantly contains various proportions of straight and branched-chain paraffins, cycloparaffins, and naphthenic, aromatic, and polynuclear aromatic hydrocarbons. These hydrocarbons can be gaseous, liquid, or solid under normal conditions of temperature and pressure, depending on the number and arrangement of carbon atoms in the molecules.

Crude oils vary widely in their physical and chemical properties from one geographical region to another and from field to field. Crude oils are usually classified into three groups according to the nature of the hydrocarbons they contain: paraffinic, naphthenic, asphaltic, and their mixtures. The differences are due to the different proportions of the various molecular types and sizes. One crude oil can contain mostly paraffins, another mostly naphthenes. Whether paraffinic or naphthenic, one can contain a large quantity of lighter hydrocarbons and be mobile or contain dissolved gases; another can consist mainly of heavier hydrocarbons and be highly viscous, with little or no dissolved gas. Crude oils can also include heteroatoms containing sulfur, nitrogen, nickel, vanadium and other elements in quantities that impact the refinery processing of the crude oil fractions. Light crude oils or condensates can contain sulfur in concentrations as low as 0.01 W %; in contrast, heavy crude oils can contain as much as 5-6 W %. Similarly, the nitrogen content of crude oils can range from 0.001-1.0 W %.

The nature of the crude oil governs, to a certain extent, the nature of the products that can be manufactured from it and their suitability for special applications. A naphthenic crude oil will be more suitable for the production of asphaltic bitumen, a paraffinic crude oil for wax. A naphthenic crude oil, and even more so an aromatic one, will yield lubricating oils with viscosities that are sensitive to temperature. However, with modern refining methods there is greater flexibility in the use of various crude oils to produce many desired type of products.

A crude oil assay is a traditional method of determining the nature of crude oils for benchmarking purposes. Crude oils are subjected to true boiling point (TBP) distillations and fractionations to provide different boiling point fractions. The crude oil distillations are carried out using the American Standard Testing Association (ASTM) Method D 2892. Common fractions and their corresponding nominal boiling points or boiling point ranges are given in Table 1.

The yields, composition, physical and indicative properties of these crude oil fractions, where applicable, are then determined during the crude assay work-up calculations. Typical compositional and property information obtained from a crude oil assay is given in Table 2.

Due to the number of distillation cuts and the number of analyses involved, the crude oil assay work-up is both costly and time consuming. In a typical refinery, crude oil is first fractionated in the atmospheric distillation column to separate sour gas and light hydrocarbons, including methane, ethane, propane, butanes and hydrogen sulfide, naphtha (for instance having a nominal boiling point range of about 36-180° C.), kerosene (for instance having a nominal boiling point range of about 180-240° C.), gas oil (for instance having a nominal boiling point range of about 240-370° C.) and atmospheric residue (for instance having a nominal boiling point range of about >370° C.). The atmospheric residue from the atmospheric distillation column is either used as fuel oil or sent to a vacuum distillation unit, depending on the configuration of the refinery. The principal products obtained from vacuum distillation are vacuum gas oil (for instance having a nominal boiling point range of about 370-520° C.) and vacuum residue (for instance having a nominal boiling point range of about >520° C.). Crude assay data is conventionally obtained from individual analysis of these cuts, separately for each type of data sought for the assay (that is, elemental composition, physical property and indicative property), to help refiners to understand the general composition of the crude oil fractions and properties so that the fractions can be processed most efficiently and effectively in an appropriate refining unit. Indicative properties are used to determine the engine/fuel performance or usability or flow characteristic or composition.

Whole Crude Oil Properties

Many properties are routinely measured for crudes. Some of the most common factors affecting crude oil handling, processing, and value include the following: density; viscosity; pour point; Reid vapor pressure (RVP); carbon residue; sulfur; nitrogen; metals; salt content; hydrogen sulfide; Total Acidity Number (TAN). These are described in more detail below:

-   -   Density, measured for example by the ASTM D287 method, is the         weight of a substance for a given unit of volume. Density of         crude oil or crude products is measured as specific gravity         comparing the density of the crude or product to the density of         water (usually expressed as gm/cc) or API gravity (° API or         degrees API).     -   Viscosity, measured for example by the ASTM D 445 method, is the         measure of the resistance of a liquid to flow, thereby         indicating the pumpability of the oil. Kinematic viscosity is         the viscosity of the material divided by the density (specific         gravity) of the material at the temperature of viscosity         measurement; kinematic viscosity is commonly measured in stokes         (St) or centistokes (cSt).     -   Pour point, measured for example by the ASTM D97 method, is the         temperature, to the next 5° F. increment, above which an oil or         distillate fuel becomes solid. The pour point is also the lowest         temperature, in 5° F. increments, at which the fluid will flow.         After preliminary heating, the sample is cooled at a specified         rate and examined at intervals of 3° C. for flow         characteristics. The lowest temperature at which movement of the         specimen is observed is recorded as the pour point.     -   Reid vapor pressure (RVP), measured for example by the ASTM D323         method, is the measure of the vapor pressure exerted by an oil,         mixed with a standard volume ratio of air, at 100° F. (38° C.).     -   Carbon residue, measured for example by the ASTM D189, D4536         methods, is the percentage of carbon by weight for coke,         asphalt, and heavy fuels found by evaporating oil to dryness         under standard laboratory conditions. Carbon residue is         generally termed Conradson Carbon Residue, or CCR.     -   Sulfur is the percentage by weight, or in parts per million by         weight, of total sulfur contained in a liquid hydrocarbon         sample. Sulfur must be removed from refined product to prevent         corrosion, protect catalysts, and prevent environmental         pollution. Sulfur is measured, for example, by ASTM D4294,         D2622, D5453 methods for gasoline and diesel range hydrocarbons.     -   Nitrogen, measured for example by the ASTM D4629, D5762 methods,         is the weight in parts per million, of total nitrogen contained         in a liquid hydrocarbon sample. Nitrogen compounds are also         catalyst poisons.     -   Various metals (arsenic, lead, nickel, vanadium, etc.) in a         liquid hydrocarbon are potential process catalyst poisons. They         are measured by Induced Coupled Plasma and/or Atomic Absorption         Spectroscopic methods, in ppm.     -   Salt is measured, for example, by the ASTM D3230 method and is         expressed as pounds of salt (NaCl) per 1000 barrels of crude.         Salts are removed prior to crude oil distillation to prevent         corrosion and catalyst poisoning.     -   Hydrogen sulfide (H₂S) is a toxic gas that can be evolved from         crude or products in storage or in the processing of crude.         Hydrogen sulfide dissolved in a crude stream or product stream         is measured in ppm.     -   Total acidity is measured, for example, by the ASTM methods,         D664, D974, and is a measure of the acidity or alkalinity of an         oil. The number is the mass in milligrams of the amount of acid         (HCl) or base (KOH) required to neutralize one gram of oil.

These properties affect the transportation and storage requirements for crudes, define the products that can be extracted under various processing schemes, and alert us to safety and environmental concerns. Each property can also affect the price that the refiner is willing to pay for the crude. In general, light, low sulfur crudes are worth more than heavy, high sulfur crudes because of the increased volume of premium products (gasoline, jet fuel, and diesel) that are available with minimum processing.

Crude Assays

A crude assay is a set of data that defines crude composition and properties, yields, and the composition and properties of fractions. Crude assays are the systematic compilation of data defining composition and properties of the whole crude along with yields and composition and properties of various boiling fractions. For example, a conventional assay method requires approximately 20 liters of crude oil be transported to a laboratory, which itself can be time-consuming and expensive, and then distilled to obtain the fractions and then have analysis performed on the fractions. This systematic compilation of data provides a common basis for the comparison of crudes. The consistent presentation of data allows us to make informed decisions as to storage and transportation needs, processing requirements, product expectations, crude relative values, and safety and environmental concerns. It also allows us to monitor crude quality from a single individual source over a period of time.

Crude oils or fractions are evaluated and compared using some of the key properties that are indicative of their performance in engines. These are the cetane number, the cloud point, the pour point (discussed above), the aniline point, and the flash point. In instances where the crude is suitable for production of gasoline, the octane number is another key property. These are described individually herein.

The cetane number of diesel fuel oil, determined by the ASTM D613 method, provides a measure of the ignition quality of diesel fuel; as determined in a standard single cylinder test engine; which measures ignition delay compared to primary reference fuels. The higher the cetane number; the easier the high-speed; direct-injection engine will start; and the less white smoking and diesel knock after start-up are. The cetane number of a diesel fuel oil is determined by comparing its combustion characteristics in a test engine with those for blends of reference fuels of known cetane number under standard operating conditions. This is accomplished using the bracketing hand wheel procedure which varies the compression ratio (hand wheel reading) for the sample and each of the two bracketing reference fuels to obtain a specific ignition delay, thus permitting interpolation of cetane number in terms of hand wheel reading.

The cloud point, determined by the ASTM D2500 method, is the temperature at which a cloud of wax crystals appears when a lubricant or distillate fuel is cooled under standard conditions. Cloud point indicates the tendency of the material to plug filters or small orifices under cold weather conditions. The specimen is cooled at a specified rate and examined periodically. The temperature at which cloud is first observed at the bottom of the test jar is recorded as the cloud point. This test method covers only petroleum products and biodiesel fuels that are transparent in 40 mm thick layers, and with a cloud point below 49° C.

The aniline point, determined by the ASTM D611 method, is the lowest temperature at which equal volumes of aniline and hydrocarbon fuel or lubricant base stock are completely miscible. A measure of the aromatic content of a hydrocarbon blend is used to predict the solvency of a base stock or the cetane number of a distillate fuel. Specified volumes of aniline and sample, or aniline and sample plus n-heptane, are placed in a tube and mixed mechanically. The mixture is heated at a controlled rate until the two phases become miscible. The mixture is then cooled at a controlled rate and the temperature at which two separate phases are again formed is recorded as the aniline point or mixed aniline point.

The flash point, determined by ASTM D56, D92, D93 methods, is the minimum temperature at which a fluid will support instantaneous combustion (a flash) but before it will burn continuously (fire point). Flash point is an important indicator of the fire and explosion hazards associated with a petroleum product.

The octane number, determined by the ASTM D2699 or D2700 methods, is a measure of a fuel's ability to prevent detonation in a spark ignition engine. Measured in a standard single-cylinder; variable-compression-ratio engine by comparison with primary reference fuels. Under mild conditions, the engine measures research octane number (RON), while under severe conditions, the engine measures motor octane number (MON). Where the law requires posting of octane numbers on dispensing pumps, the antiknock index (AKI) is used. This is the arithmetic average of RON and MON, (R+M)/2. It approximates the road octane number, which is a measure of how an average car responds to the fuel.

New rapid, and direct methods to help better understand crude oil compositions and properties from analysis of whole crude oil will save producers, marketers, refiners and/or other crude oil users substantial expense, effort and time. Therefore, a need exists for an improved system and method for determining indicative properties of crude oil fractions from different sources.

SUMMARY

Systems and methods are disclosed for providing virtual assays including assigned assay values pertaining to an oil sample subject to analysis, and its fractions, based on data obtained by analytic characterization of the oil sample without fractionation, and the density of the oil sample. The virtual assay of the oil sample provides a full range of information about fractions of the oil sample including naphtha, gas oil, vacuum gas oil, residue, and other information about the properties of the oil sample. This virtual assay is useful for producers, refiners, and marketers to benchmark the oil quality and, as a result, evaluate the oils without performing the customary extensive and time-consuming crude oil assays.

In an embodiment, the present disclosure is directed to a method for producing a virtual assay of an oil sample, wherein the oil sample is characterized by a density, selected from the group consisting of crude oil, bitumen and shale oil, and characterized by naphtha, gas oil, vacuum gas oil and vacuum residue fractions. Gel permeation chromatography (GPC) data indicative of GPC peak intensity values at predetermined GPC retention time increments between a predetermined range of GPC retention times for a solution of the oil sample without distillation in a GPC solvent, is entered into a computer. An analytical value (AV) is calculated and assigned as a function of the GPC data. Virtual assay data of the oil sample and the naphtha, gas oil, vacuum gas oil and vacuum residue fractions is calculated and assigned as a function of the AV and the density of the oil sample. The virtual assay data comprises a plurality of assigned data values.

In certain embodiments, the virtual assay data comprises: a plurality of assigned assay data values pertaining to the oil sample including one or more of the aromatic content, C5-asphaltenes content, elemental compositions of sulfur and nitrogen, micro-carbon residue content, total acid number and viscosity, a plurality of assigned assay values pertaining to the vacuum residue fraction of the oil sample including one or more of the elemental composition of sulfur and micro-carbon residue content; a plurality of assigned assay values pertaining to the vacuum gas oil fraction of the oil sample including one or both of the elemental compositions of sulfur and nitrogen; a plurality of assigned assay values pertaining to the gas oil fraction of the oil sample including one or more of the elemental compositions of sulfur and nitrogen, viscosity, and indicative properties including aniline point, cetane number, cloud point and/or pour point; and a plurality of assigned assay values pertaining to the naphtha fraction of the oil sample including one or more of the aromatic content, elemental composition of hydrogen and/or sulfur, paraffin content and octane number.

In certain embodiments, the virtual assay data also comprises: yields of fractions from the oil sample as mass fractions of boiling point ranges, including one or more of naphtha, gas oil, vacuum gas oil and vacuum residue; composition information of hydrogen sulfide and/or mercaptans in the oil sample and/or its fractions; elemental compositions of one or more of carbon, hydrogen, nickel, and vanadium; physical properties of the oil sample and/or its fractions including one or more of API gravity and refractive index; and/or indicative properties of the oil sample and/or its fractions including one or more of flash point, freezing point and smoke point.

In certain embodiments, the method further comprises analyzing the solution of the oil sample without distillation in a GPC solvent by gel permeation chromatography to obtain the GPC data.

In certain embodiments, each assay value is determined by a multi-variable polynomial equation with predetermined constant coefficients developed using linear regression techniques, wherein corresponding variables are the AV and the density of the oil sample.

In certain embodiments, the analytical value is a GPC Index derived from a summation of GPC peak intensities obtained at plural GPC retention times over a range of GPC retention times. In certain embodiments, the analytical value is a GPC Index derived from a summation of GPC peak intensities multiplied by a corresponding molecular weight, over a range of molecular weights, where the molecular weights are obtained as a function of the GPC retention time.

In an embodiment, the present disclosure is directed to a system for producing a virtual assay of an oil sample, wherein the oil sample is characterized by a density, is selected from the group consisting of crude oil, bitumen and shale oil, and is characterized by naphtha, gas oil, vacuum gas oil and vacuum residue fractions. The system comprises a gel permeation chromatography (GPC) system that outputs GPC data, a non-volatile memory device, a processor coupled to the non-volatile memory device, and first and second calculation modules that are stored in the non-volatile memory device and that are executed by the processor. The non-volatile memory device stores the calculation module and data, the data including the GPC data that is indicative of intensity values at predetermined GPC retention time increments between a predetermined range of GPC retention times for a solution of the oil sample without distillation in a GPC solvent. The first calculation module contains suitable instructions to calculate, as a function of the GOC data, one or more analytical values (AV). The second calculation module contains suitable instructions to calculate, as a function of the one or more AVs and the density of the oil sample, a plurality of assigned data values as the virtual assay pertaining to the overall oil sample, and the naphtha, gas oil, vacuum gas oil and vacuum residue fractions of the oil sample.

Still other aspects, embodiments, and advantages of these exemplary aspects and embodiments, are discussed in detail below. Moreover, it is to be understood that both the foregoing information and the following detailed description are merely illustrative examples of various aspects and embodiments, and are intended to provide an overview or framework for understanding the nature and character of the claimed aspects and embodiments. The accompanying drawings are included to provide illustration and a further understanding of the various aspects and embodiments, and are incorporated in and constitute a part of this specification. The drawings, together with the remainder of the specification, serve to explain principles and operations of the described and claimed aspects and embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is process flow diagram of steps used to implement the method described herein for providing virtual assays of an oil sample such as crude oil based on gel permeation chromatography (GPC).

FIG. 2A is a graphic plot of typical GPC data for three types of crude oil as oil samples.

FIG. 2B is a plot of a correlation of GPC retention time index according to embodiments herein relative to the average molecular weight (MW at 50% point) of types of crude oil as oil samples including an oil sample under investigation in the example herein.

FIG. 3 is a process flow diagram of steps used in an example herein to provide a virtual assay of a crude oil sample based on GPC.

FIG. 4 is a block diagram of a component of a system for implementing the invention, according to one embodiment.

DETAILED DESCRIPTION

Systems and methods are disclosed for providing virtual assays of an oil sample such as crude oil based on gel permeation chromatography (GPC) carried out on the oil sample or a solution of the oil sample in a GPC solvent, and the density of the oil sample. The virtual assay provides a full range of information about fractions of the oil sample including naphtha, gas oil, vacuum gas oil, vacuum residue, and other information about the properties of the oil sample. Using the system and method herein, the virtual assay data pertaining to these several fractions of the oil sample and the oil sample itself are obtained without fractionation of the oil sample into the several components.

Concerning the naphtha fraction, assigned assay values for the virtual assay include: elemental composition values included in the virtual assay comprise one or more of hydrogen content, aromatic content, paraffin content and sulfur content; and an indicative property included in the virtual assay comprises an octane number. Concerning the gas oil fraction, assigned assay values for the virtual assay include: elemental composition values included in the virtual assay comprise one or more of sulfur content and nitrogen content; physical properties included in the virtual assay comprises viscosity and pour point; and indicative properties included in the virtual assay comprise one or more of aniline point, cetane number and cloud point. Concerning the vacuum gas oil fraction, assigned assay values for the virtual assay include: elemental composition values included in the virtual assay comprise one or more of sulfur content, nitrogen content and micro carbon residue content. Concerning the vacuum residue, assigned assay values for the virtual assay include: elemental composition values included in the virtual assay comprise one or more of sulfur content and micro carbon residue content. Concerning the full range of the oil sample, assigned assay values for the virtual assay include: elemental composition values included in the virtual assay comprise one or more of asphaltene content, sulfur content, nitrogen content and total acids content (total acid number, mg KOH/100 g); and physical properties included in the virtual assay comprises viscosity and pour point.

In certain embodiments of the virtual assay provided herein, the “naphtha fraction” refers to a straight run fractions from atmospheric distillation containing hydrocarbons having a nominal boiling range of about 20-205, 20-193, 20-190, 20-180, 20-170, 32-205, 32-193, 32-190, 32-180, 32-170, 36-205, 36-193, 36-190, 36-180 or 36-170° C.; the “gas oil fraction” refers to a straight run fractions from atmospheric distillation containing hydrocarbons having a nominal boiling range of about 170-400, 170-380, 170-370, 170-360, 180-400, 180-380, 180-370, 180-360, 190-400, 190-380, 190-370, 190-360, 193-400, 193-380, 193-370 or 193-360° C.; the “vacuum gas oil fraction” refers to a straight run fractions from vacuum distillation containing hydrocarbons having a nominal boiling range of about 360-565, 360-550, 360-540, 360-530, 360-520, 360-510, 370-565, 370-550, 370-540, 370-530, 370-520, 370-510, 380-565, 380-550, 380-540, 380-530, 380-520, 380-510, 400-565, 400-550, 400-540, 400-530, 400-520 or 400-510° C.; and “vacuum residue” refers to the bottom hydrocarbons from vacuum distillation having an initial boiling point corresponding to the end point of the VGO range hydrocarbons, for example about 510, 520, 530, 540, 550 or 565° C., and having an end point based on the characteristics of the crude oil feed.

The system and method is applicable for naturally occurring hydrocarbons derived from crude oils, bitumens or shale oils, and heavy oils from refinery process units including hydrotreating, hydroprocessing, fluid catalytic cracking, coking, and visbreaking or coal liquefaction. Samples can be obtained from various sources, including an oil well, core cuttings, oil well drilling cuttings, stabilizer, extractor, or distillation tower. In certain embodiments system and method is applicable for crude oil, whereby a virtual assay is obtained using the systems and methods herein without the extensive laboratory work required for distillation and analysis of each of the individual fractions.

Referring to FIG. 1 , a process flow diagram of steps carried out to obtain a virtual assay 195 is provided. Prior to carrying out the steps outlined in FIG. 1 , a set of constants is obtained for each of the elemental composition values/physical properties/indicative properties to be calculated using the process and system disclosed herein to obtain a virtual assay, represented as dataset 105. The set of constants can be developed, for instance by linear regression techniques, based on empirical data of a plurality of crude oil assays and analyses using conventional techniques including distillation and industry-established testing methods to obtain the crude oil assay data. Examples of sets of constants used for calculating assigned assay values to produce the virtual assay 195 based on various analytic characterization techniques are provided herein.

At step 110, the density if the oil sample is provided (steps for obtaining this density are not shown and can be carried out as is known, in certain embodiments a 15° C./4° C. density in units of kilograms per liter using the method described in ASTM D4052); this density value can be stored in memory with other data pertaining to the oil sample, or conveyed directly to the one or more steps as part of the functions thereof. In step 115, if necessary, the oil sample is prepared for a particular analytic characterization technique (shown in dashed lines as optional). In step 120, analytic characterization of the oil sample, or the oil sample prepared as in step 115, without fractionation, is carried out. As a result, analytic characterization data 125 is obtained.

In step 130, the analytic characterization data 125 is used to calculate one or more analytical values 135, which are one common analytical value or a common set of analytical values used in subsequent steps to calculate a plurality of different elemental composition values/physical properties/indicative properties that make up the virtual assay. In the embodiments herein the one common analytical value or common set of analytical values is an index or plural index values, also referred to as a GPC index (GPCI), that is based on GPC data. According to an embodiment the GPC index is derived from a summation of GPC peak intensity values over a range of GPC retention times. According to an embodiment the GPC index is derived from a summation of GPC peak intensity values multiplied by the molecular weight, over a range of molecular weights, where the molecular weights are obtained as a function of the GPC retention time.

Steps 140, 150, 160, 170 and 180 are used to calculate and assign a plurality of different elemental composition values/physical properties/indicative properties that make up the virtual assay 195, for each of a total oil sample, a naphtha fraction, a gas oil fraction, a vacuum gas oil fraction and a vacuum residue fraction, respectively. Each of the steps produces corresponding assigned assay values for the virtual assay 195, include including assigned assay values 145 pertaining to the total oil sample, assigned assay values 155 pertaining to a naphtha fraction, assigned assay values 165 pertaining to a gas oil fraction, assigned assay values 175 pertaining to a vacuum gas oil fraction and assigned assay values 185 pertaining to a vacuum residue fraction.

In certain embodiments, the steps are carried out in any predetermined sequence, or in no particular sequence, depending on the procedures in the calculation modules. In certain embodiments, the steps are carried out in parallel. The process herein uses a common analytical value, in conjunction with the set of constants and the density of the oil sample, for each of the assigned assay values (elemental composition values/physical properties/indicative properties) in the given virtual oil sample assay 195 produced at step 190. For instance, each of the steps 140, 150, 160, 170 and 180 are carried in any sequence and/or in parallel out as show using the equations herein for various analytical values or sets of analytical values.

The assigned assay values from each of the fractions and the total oil sample are compiled and presented as a virtual assay 195, which can be, for instance, printed or rendered on a display visible to, or otherwise communicated to, a user to understand the composition and properties of the crude. With the virtual assay 195, users such as customers, producers, refiners, and marketers can benchmark the oil quality. The virtual assay 195 can be used to guide decisions related to an appropriate refinery or refining unit, for processing the oil from which the oil sample is obtained, and/or for processing one or more of the fractions thereof. In addition the assigned assay values including the indicative properties are used to determine the engine/fuel performance or usability or flow characteristic or composition. This can be accomplished using the method and system herein without performing the customary extensive and time-consuming crude oil assays.

The assigned assay values for the virtual assay herein are calculated as a function of one or more analytical values, and the density of the oil sample, as denoted at (1).

AD=f(ρ,AV)  (1)

where:

-   -   AD is the assigned assay value (for example a value and/or         property representative of an elemental composition value, a         physical property or an indicative property);     -   AV is an analytical value of the oil sample, wherein AV can be a         single analytical value, or wherein AV can be AV(1) . . . AV(n)         as plural analytical values of the oil sample, wherein n is an         integer of 2 or more, in certain embodiments 2, 3 or 4; and     -   ρ is the density of the oil sample, in certain embodiments a 15°         C./4° C. density in units of kilograms per liter using the         method described in ASTM D4052.

According to an embodiment of the system and method described further herein, an analytical value AV is a GPC index derived from a summation of GPC peak intensities (in arbitrary units, a.u.) obtained at plural GPC retention times over a range of GPC retention times. According to an embodiment of the system and method described further herein, an analytical value AV is a GPC index derived from a summation of GPC peak intensities multiplied by the corresponding molecular weight, over a range of molecular weights, where the molecular weights are obtained as a function of the GPC retention time.

Advantageously, the method and system herein deploy analytical characterization by GPC to carry out analysis of the oil sample without fractionating, obtain an analytical value based on the GPC analysis of the oil sample, and use the analytical value or set of analytical values, and the density of the oil sample to obtain a plurality of assigned assay values (for example a value and/or property representative of an elemental composition value, a physical property or an indicative property) to produce a virtual assay of the oil sample.

In one embodiment, an assigned assay value is calculated used a third degree multi variable polynomial equation including the analytical value, the density of the oil sample, and a plurality of constants, for example predetermined by linear regression, as denoted in equation (2a).

AD=K _(AD) +X1_(AD)*AV+X2_(AD)*AV² +X3_(AD)*AV³ +X4_(AD)*ρ*AV  (2a)

where:

-   -   AD is the assigned assay value (for example a value and/or         property representative of an elemental composition value, a         physical property or an indicative property);     -   AV is an analytical value of the oil sample;     -   ρ is the density of the oil sample, in certain embodiments a 15°         C./4° C. density in units of kilograms per liter using the         method described in ASTM D4052; and     -   K_(AD), X1_(AD), X2_(AD), X3_(AD), and X4_(AD) are constants,         for instance, developed using linear regression techniques (note         that in certain embodiments and for certain assigned assay         values, one or more of K_(AD), X1_(AD), X2_(AD), X3_(AD) and         X4_(AD) is/are not used, or is/are zero).

In another embodiment, an assigned assay value is calculated used a third degree multi variable polynomial equation including the analytical value, the density of the oil sample, and a plurality of constants, for example predetermined by linear regression, as denoted in equation (2b).

AD=K _(AD) +X1_(AD) *ρ+X2_(AD)*ρ² +X3_(AD)*ρ³ +X4_(AD)*AV+X5_(AD)*AV² +X6_(AD)*AV³ +X7_(AD)*ρ*AV  (2b)

where:

-   -   AD is the assigned assay value (for example a value and/or         property representative of an elemental composition value, a         physical property or an indicative property);     -   AV is an analytical value of the oil sample;     -   ρ is the density of the oil sample, in certain embodiments a 15°         C./4° C. density in units of kilograms per liter using the         method described in ASTM D4052; and     -   K_(AD), X1_(AD), X2_(AD), X3_(AD), X4_(AD), X5_(AD), X6_(AD) and         X7_(AD) are constants, for instance, developed using linear         regression techniques (note that in certain embodiments and for         certain assigned assay values, one or more of K_(AD), X1_(AD),         X2_(AD), X3_(AD), X4_(AD), X5_(AD), X6_(AD) and X7_(AD) is/are         not used, or is/are zero).

Assigned assay values that can be determined and included for display or presentation to the user in the virtual assay produced using the systems and methods herein include one or more of:

-   -   elemental composition of the oil sample and its fractions         including the sulfur and nitrogen compositions;     -   TAN (total acid number) of the oil sample;     -   composition of certain desirable and undesirable compounds or         types of compounds present in the oil sample and/or its         fractions, including one or more of, micro carbon residue,         C5-asphaltenes (the yield of asphaltenes using separation based         on C5 paraffins as deasphalting solvent), paraffins, aromatics,         and naphthenes;     -   physical properties of the oil sample and/or its fractions         including viscosity such as kinematic viscosity;     -   indicative properties of the oil sample and/or its fractions,         including one or more of cloud point, pour point, research         octane number, cetane number and aniline point.         In certain embodiments, the assigned assay values can include         yields of fractions from the oil sample, for example as mass         fractions of boiling point ranges, including one or more of         naphtha, gas oil, vacuum gas oil and vacuum residue. In certain         embodiments, the assigned assay values can include composition         information of hydrogen sulfide and/or mercaptans in the oil         sample and/or its fractions. In certain embodiments, the         assigned assay values can include elemental compositions of one         or more of carbon, hydrogen, nickel, and vanadium. In certain         embodiments, the assigned assay values can include physical         properties of the oil sample and/or its fractions including one         or more of API gravity and refractive index. In certain         embodiments, the assigned assay values can include indicative         properties of the oil sample and/or its fractions including one         or more of flash point, freezing point and smoke point.

In certain embodiments, a method for producing a virtual assay of an uncharacterized oil sample is provided. The uncharacterized oil sample is characterized by a density, selected from the group consisting of crude oil, bitumen and shale oil, and characterized by naphtha, gas oil, vacuum gas oil and vacuum residue fractions. The virtual assay comprises a plurality of assigned data values. The uncharacterized oil sample is obtained, for instance the sample being between one to two milliliters in volume and not subject to any fractionation. A plurality of known data values (corresponding to the assigned data values used in the virtual assay) for known oil samples with known densities (which known oil samples exclude the uncharacterized oil sample) are obtained. This data is obtained from empirical data of a plurality of existing crude oil assays and/or analyses using conventional techniques including distillation and industry-established testing methods. One or more selected analytical techniques are carried out on the each of the known oil samples, and one or more analytical values are calculated for each of the known oil samples. The one or more selected analytical techniques are carried out on the uncharacterized oil sample, and one or more analytical values are calculated for the uncharacterized oil sample. Constants of a polynomial equation are obtained, and the polynomial equation is used to determine a plurality of assigned data values that make up the virtual assay of the uncharacterized oil sample. The polynomial equation is a function of density and the one or more analytical values of the uncharacterized oil sample. The constants of the polynomial equation are determined using a fitting method to fit the plurality of known data values of the plurality of known oil samples to the plurality of values of the density of the plurality of known oil samples and the plurality of the one or more analytical values for the plurality of known oil samples.

Rather than relying on conventional techniques including distillation and laborious, costly and time-consuming analytical methods to measure/identify data regarding the crude oil and/or its fractions including elemental composition, physical properties and indicative properties, as little as 1 gram of oil can be analyzed. From the analysis of a relatively small quantity of the oil sample, the assigned assay values are determined by direct calculation, without requiring distillation/fractionization.

Gel permeation chromatography is the analytic characterization technique that is employed on a relatively small quality of an oil sample, such as crude oil. An analytical value, comprising or consisting of the GCP index, from said analytic characterization technique, is used to calculate and assign physical and indicative properties that are the requisite data for the virtual oil sample assay. The method and system provides insight into the properties of oil sample, the naphtha fraction, the gas oil fraction, the vacuum gas oil fraction, and the vacuum residue fraction, without fractionation/distillation (conventional crude oil assays). The virtual oil sample assay will help producers, refiners, and marketers benchmark the oil quality and, as a result, evaluate (qualitatively and economically) the oils without going thru costly and time consuming crude oil assays. Whereas a conventional crude oil assay method could take up to two months, the method and system herein can provide a virtual assay in less than one day and in certain embodiments less than 1-2 hours. In addition, the method and system herein carried out at 1% or less of the cost of a traditional assay requiring distillation/fractionization follows by individual testing for each type of property and for each fraction.

The systems and methods herein are implemented using an index derived from GPC data as an analytical value in equations (1), and (2a) or (2b), above. Embodiments of such methods are described in the context of assigning an indicative property to a fraction of an oil sample in commonly owned US20200116683A1, which is incorporated by reference herein in its entirety. In the systems and methods herein, and with reference to FIG. 1 , a virtual assay 195 of an oil sample is obtained at step 190, wherein each assigned data value of the virtual assay is a function of an index derived from GPC data based on analysis of the oil sample (or in another embodiment, as a function of the density of the oil sample and of an index derived from GPC data based on analysis of the oil sample). The virtual assay provides information about the oil sample and fractions thereof to help producers, refiners, and marketers benchmark the oil quality and, as a result, evaluate the oils without performing the customary extensive and time-consuming crude oil assays involving fractionation/distillation and several individual and discrete tests.

The oil sample is optionally prepared, step 115, by dissolving the oil sample in a suitable solvent for gel permeation chromatography, referred to as a GPC solvent. Such GPC solvents include but are not limited to tetrahydrofuran, dimethylacetamide, N-methyl-2-pyrrolidone, hexafluorisopropanol, butylated hydroxytoluene, dimethylformamide, dimethylsulfoxide, 1,2,4-trichlorobenzene, sodiumtrifluoroacetate or triethylamine. Other suitable polar solvents can also be used.

The solution is analyzed, step 120, and GPC data is obtained. Step 120 is carried out and the analytic characterization data, the GPC data, is entered into the computer system 400 described herein with respect to FIG. 4 , for example stored into non-volatile memory of the via data storage memory 480, represented as the analytic characterization data 125. This can be carried out by a raw data receiving module stored in the program storage memory 470.

An analytical value is obtained, step 130, from the GPC data. In certain embodiments, a single analytical value is obtained, a GPC index. According to an embodiment of the system and method described further herein, a GPC index derived from a summation of GPC peak intensities (in arbitrary units, a.u.) obtained at plural GPC retention times over a range of GPC retention times. In certain embodiments a range of GPC retention times is about 22 minutes to 29 minutes.

According to an embodiment of the system and method described further herein, an analytical value is a GPC index derived from a summation of GPC peak intensities multiplied by the corresponding molecular weight, over a range of molecular weights, where the molecular weights are obtained as a function of the GPC retention time. In certain embodiments a range of molecular weights is 150 g/gmol to 900 g/gmol. To obtain equivalent molecular weights for the GPC retention time, a GPC retention time index, GPCRTI, is obtained at each GPC retention time, which is converted to molecular weight, and a GPC index is calculated from gel permeation chromatography data and the molecular weight. Step 130 is carried out, for example, by execution by the processor 420 of one or more modules stored in the program storage memory 470, and the analytical values 135, the index, is stored in the program storage memory 470 or the data storage memory 480, for use in the modules determining the assigned data values. In certain embodiments, the density of the oil sample, provided at step 110, is stored in the program storage memory 470 or the data storage memory 480, for use in the modules determining the assigned data values; this can be carried out by a raw data receiving module stored in the program storage memory 470.

The assigned data values including virtual assay data 145 pertaining to the total oil sample, virtual assay data 155 pertaining to a naphtha fraction, virtual assay data 165 pertaining to a gas oil fraction, virtual assay data 175 pertaining to a vacuum gas oil fraction and virtual assay data 185 pertaining to a vacuum residue fraction, are obtained according to the functions described herein, for example, in the corresponding steps 140, 150, 160, 170 and 180. The constants used for determining the assigned data values, are provided at step 105 and are stored in the program storage memory 470 or the data storage memory 480, for use in the modules determining the assigned data values. The steps for obtaining the assigned data values are carried out, for example, by execution by the processor 420 of one or more modules stored in the program storage memory 470, and the several assigned data values are calculated and stored in the data storage memory 480, presented on the display 410 and/or presented to the user by some other output device such as a printer.

GPC is a technique commonly used to separate compounds based on the size in solution, and is also referred to as size-exclusion chromatography. A method using GPC has been used to determine the boiling point distribution of high boiling petroleum fractions (Grzegorz Boczkaj, Andrzej Przyjazny, Marian Kaminski “Size-exclusion chromatography for the determination of the boiling point distribution of high-boiling petroleum fractions” J. Sep. Sci. 2015, 38, 741-748.). The method was compared with ASTM D2887 and was found to be superior for the determination of final boiling point values of high boiling mixtures up to about 550° C. The GPC method is further improved to be suitable for crude oils of various origins.

A suitable GPC system to obtain the GPC data herein includes instrumentation incorporating a pump, an injector, a column set and a detector. As is known in the art, instruments such as liquid chromatography or high performance liquid chromatography (HPLC) units can be adapted to operate as a GPC system.

The virtual assay values are assigned as a function of the density and the GPCI of the oil sample such as crude oil. The determination of the assigned data is carried out using variables comprising or consisting of the GPCI of the oil sample and the density of the oil sample.

AD=f(ρ,GPCI))  (3)

where:

-   -   AD is the assigned data value (for example a value and/or         property representative of an elemental composition value, a         physical property or an indicative property);     -   GPCI=index derived from a summation of GPC peak intensities over         a range of GPC retention times, or derived from a summation of         GPC peak intensities multiplied by molecular weight over a range         of molecular weights, where the molecular weights are obtained         as a function of the GPC retention time; and     -   ρ is the density of the oil sample, in certain embodiments a 15°         C./4° C. density in units of kilograms per liter using the         method described in ASTM D4052.

For example, this relationship can be expressed as follows:

AD=K _(AD) +X1_(AD) *ρ+X2_(AD)*ρ² +X3_(AD)*ρ³ +X4_(AD)*GPCI+X5_(AD)*GPCI² +X6_(AD)*GPCI³ +X7_(AD)*ρ*GPCI  (4)

where AD, GPCI and p are as in equation (3), and where:

-   -   K_(AD), X1_(AD), X2_(AD), X3_(AD), X4_(AD), X5_(AD), X6_(AD) and         X7_(AD) are constants, for instance, developed using linear         regression techniques, for each AD to be determined (note that         in certain embodiments and for certain assigned assay values,         one or more of K_(AD), X1_(AD), X2_(AD), X3_(AD), X4_(AD),         X5_(AD), X6_(AD) and X7_(AD) is/are not used, or is/are zero).

Using the equation (4), one or more assigned data values AD are determined using the density of the oil sample and the GPCI of the oil sample, as determined by GPC data of the oil sample.

Table 3 lists assigned data for a virtual assay of an oil sample under investigation, with descriptions, abbreviations and units, for each assigned data property for the naphtha fraction, the gas oil fraction, the vacuum gas oil fraction, the vacuum residue fraction and the overall oil sample. Table 3 further provides exemplary constants, for instance, developed using linear regression techniques, for plural assigned data values to be determined based on the density of the oil sample and the GPCI of the oil sample. These constants are used in the example below with the calculated values provided in Table 5 compared to the actual values as determined by a conventional crude oil assay.

The constants, for example as in Table 3, are stored as in step 105 in the process flow diagram of FIG. 1 . These are used in one or more calculation modules to obtain the virtual assay 195 of an oil sample as in step 190, in conjunction with the analytical values obtained step 130 based upon GPC data, the GPCI of the oil sample. In certain embodiments the constants are stored as in step 105, and the density is stored as in step 110; the constants are used in one or more calculation modules to obtain the virtual assay 195 of an oil sample as in step 190, in conjunction with density of the oil sample stored in step 110 and the analytical values obtained in step 130 from the GPC data obtained in step 120, the GPCI of the oil sample. As shown, modules are separated based on the fraction for which assigned data values are obtained, but is it understood that they can be arranged in any manner so as to provide all of the assigned data values required for the virtual assay of the oil sample.

In certain embodiments, the assigned data values including virtual assay data 145 pertaining to the total oil sample, virtual assay data 155 pertaining to a naphtha fraction, virtual assay data 165 pertaining to a gas oil fraction, virtual assay data 175 pertaining to a vacuum gas oil fraction and virtual assay data 185 pertaining to a vacuum residue fraction. This data is obtained according to the function (3) described above (for example expressed as in equation (4) described above, for example, with the corresponding modules/steps 140, 150, 160, 170 and 180).

In certain embodiments, the analytical value obtained as in step 130 is a GPCI of the oil sample determined directly from the GPC retention times. As is well-known in the art, a GPC typically conducts measurements at various retention times. Accordingly, in certain embodiments, the analytical value is a GPC Index derived from a summation of GPC peak intensities obtained at plural GPC retention times over a range of GPC retention times. In one embodiment the analytical value obtained as in step 130 is a GPC Index of the oil sample determined as follows:

$\begin{matrix} {{GPCI} = {\sum\limits_{{RT} = {RT1}}^{{RT} = {RT2}}\frac{{GPC}{peak}{intensity}}{1,000,000}}} & (5) \end{matrix}$

where:

-   -   GPC peak intensity=intensity value based on analysis of the oil         sample (where the oil sample is in a GPC solvent as a solution)         at a given GPC retention time (RT), obtained over a range of GPC         retention times RT1 to RT2.         In certain embodiments, RT1 is in the range of about 21-23         minutes and RT2 is in the range of about 28-30 minutes, and the         range can be divided into about 800-1100 intervals to maintain         accuracy. The selected range of GPC retention times and number         of intervals used in the equation (5) to determine the GPCI is         also used in determining the constants in Table 3.

In certain embodiments, due to a close relation between GPC retention times and the molecular weight, the index is also a function of the molecular weight values. A GPC solvent is used to elute the components, and in certain embodiments a resulting GPC chromatogram does not have retention time on an equivalent basis, and a correlation with retention time is carried out to bring the retention times to the same basis. Accordingly, in certain embodiments, the analytical value is a GPC Index derived from a summation of GPC peak intensities multiplied by a corresponding molecular weight, over a range of molecular weights, where the molecular weights are obtained as a function of the GPC retention time. In one embodiment the analytical value obtained as in step 130 is a GPC Index of the oil sample determined as follows:

$\begin{matrix} {{GPCI} = {\sum\limits_{{MW} = {MW1}}^{{MW} = {MW2}}\frac{{GPC}{peak}{intensity} \times MW}{1,000}}} & (6) \end{matrix}$

where:

-   -   GPC peak intensity=intensity value based on analysis of the oil         sample (where the oil sample is in a GPC solvent as a solution)         at a given molecular weight, obtained over a range of molecular         weights MW1 to MW2.

When equation (6) is used, the GPC retention times are correlated to molecular weights. In one embodiment, this is carried out by using a GPC retention time index (GPCRTI) as shown below:

GPCRTI=100*(FP−RT)/(FP−FE)  (7)

where:

-   -   FP: full permeation time in minutes (retention time for         solvent);     -   RT: GPC retention time at any point in minutes; and     -   FE: full exclusion time in minutes (retention time for material         that is fully excluded from the stationary phase pores).         GPCRTI is then converted to molecular weight as shown in         equation (8):

MW=a*GPCRTI−b  (8)

wherein a and b are correlation coefficients for a given range of molecular weights. The calculated MW from equation (8) can then be used in the GCPI equation (6).

Example

Crude oil samples, including a crude oil sample as the oil sample under investigation, were analyzed by GPC analysis according to the methods described herein. FIG. 2A shows a graphic plot of typical GPC data for three types of crude oil as oil samples, where the intensity in arbitrary units is plotted against retention time in minutes. The GPC data for the sample under investigation is presented in Tables 4A and 4B, where Table 4A is a simplified tabulation of GPC retention times (RT, in minutes, as integers) and corresponding intensities (in a.u.), and Table 4B is a detailed tabulation of 972 GPC retention times (in minutes, over the range of about 22 minutes to about 29 minutes) and corresponding intensities (in a.u.). FIG. 3 shows a process flow chart of steps for a method of obtaining assigned data based on GPC data. In step 305, constants are obtained, for example corresponding to the data in Table 3. In step 310, the density of the oil sample is obtained. In the example, the oil sample is Arabian medium crude with a 15° C./4° C. density of 0.8828 Kg/L, determined using the method described in ASTM D4052. In step 315, the oil sample (crude oil) is prepared by dissolving the oil sample in a suitable solvent for GPC (tetrahydrofuran in the example). At step 320, analytic characterization of the oil sample, without fractionation, is carried out. The solution of the oil sample in the solvent is analyzed using a GPC system including Agilent Technologies high performance liquid chromatography instrument (HPLC 1200 Series) and Cirrus GPC software.

Key parameters of the GPC method are as follows:

Sample concentration 0.05 g/mL in tetrahydrofuran Flow rate 1 mL/min Detector UV diode-array detector (DAD-UV) Injection volume 100 μL Run time 37 minutes Mobile phase Tetrahydrofuran Column Three columns in series (300 × 7.8 mm, 5 μm): Phenogel 1000 Å, 100 Å and 50 Å Column oven temperature 30° C.

The sample of Arabian medium crude with a density of 0.8828 Kg/l was analyzed by GPC and the chromatography data is arranged. For instance, a series of GPC retentions times can be tabulated relative to the corresponding intensity values. A summary portion of the GPC data is presented in Table 4A, and a set of 972 values over the GPC retention times of about 22 and 29 minutes are presented in Table 4B. It is understood that during GPC, the intensities over a wider time range of data is collected. The data pertaining to chromogram is obtained and stored as the analytic characterization data in step 325. The same number of GPC retention time values and range of values were used on other samples of known crude oil to obtain the constants in Table 3 herein.

At step 330, an analytical value, the GPC index (GPCI), is calculated as a function of the intensities of the detected peaks stored in step 325, as in Equation (5) herein. For example, based on the full set of data in Table 4B, for the sample of Arabian medium crude with a density of 0.8828 Kg/l and with an API gravity value of 28.8°, the GCPI is calculated as 12.7372947.

The GPCI, stored at step 335, is applied to step 390. At step 390, Equation (4) and the constants from Table 3 are applied for each of the listed ADs, using the GPCI stored at step 335, the constants stored at step 305, and the density of the oil sample stored at step 310, as shown below. Each of the determined ADs can be added to a virtual assay of the oil sample 395. For example, this can be carried out as one step, or as plural steps, for instance, similar to steps 140, 150, 160, 170 and 180 described herein in conjunction with FIG. 1 to calculate a plurality of different elemental composition values/physical properties/indicative properties that make up the virtual assay, for each of a total oil sample, a naphtha fraction, a gas oil fraction, a vacuum gas oil fraction and a vacuum residue fraction, respectively, and to produce the virtual oil sample assay 195 at step 190.

Equation (4) is applied to each of the ADs that make up the virtual assay including those identified in Table 3, using the corresponding units. In addition, the constants denoted in Table 3 are used as the constants K_(AD), X1_(AD), X2_(AD), X3_(AD), X4_(AD), X5_(AD), X6_(AD) and X7_(AD)) in equation (4); the GPCI based on the data in Table 4B, calculated as 12.7372947 using equation (5) above, is used in equation (4); and the density ρ used in equation (4) for the of the oil sample under investigation is the 15° C./4° C. density in units of kilograms per liter using the method described in ASTM D4052, which is 0.8828 Kg/L. The calculated AD values are provided for the oil sample under investigation in Table 5, compared to the actual values obtained using a conventional crude oil assay.

Although not used in the example herein, equation (6) can be used to obtain the GPCI, for instance by converting the GPC retention times into the GPCRTI as in equation (7), where the full exclusion time in minutes is 14.05 and the full permeation time in minutes is 30.67; those GPC=RTI values are converted into molecular weights according to equation (8) for example where the correlation coefficients a and b for the range of molecular weights MW1=150 g/gmol and MW2=900 g/gmol are a=16.309 and b=147.734; and equation (6) is applied using the so-obtained molecular weights and corresponding intensities. The molecular weight relation to its GPCRTI can be obtained using fractionation of the crude oil through distillation and subsequent determination of the fractions' a) molecular weight (MW) using atmospheric pressure photo ionization time-of-flight mass spectrometry (APPI TOF-MS) and b) GPCRTI. To validate molecular weights obtained from GPC retention times as in equations (7) and (8) herein, crude oil can be separated into 27 fractions, of which the average molecular weight of each fraction is determined as its weighted average molecular weight, for instance using an APPI model Time of Flight mass spectrometer (TOF-MS). Note that other mass spectrometers could be used instead. In certain embodiments, a TOF mass spectrometer is suited so as to produce accurate molecular weight distributions. For this purpose, the mass spectral abundances of all mass signals measured in the fraction can be summed from low mass-to-charge ratio to high mass-to-charge ratio; the mass-to-charge ratio reflecting 50% of the cumulative mass spectral abundance is considered as the average MW of the fraction. Analogously, the GPCRTI of each fraction is determined using equation (7) as the GPCRTI at which cumulative 50% of the fraction had eluted from the GPC apparatus. The relation of GPCRTI with the boiling point was obtained using the fractions of the crude oil (as discussed above) and subsequent determination of the fractions' a) simulated distillation profile (SIMDIS) and b) GPCRTI. For this purpose, the SIMDIS abundance was summed from low boiling to high boiling; the atmospheric equivalent boiling point (AEBP) reflecting 50% of the cumulative mass elution from the SIMDIS apparatus was considered as the average boiling point of the fraction. The GPCRTI of each fraction has been explained above. The resulting correlation is shown in FIG. 2B.

FIG. 4 shows an exemplary block diagram of a computer system 400 in which one embodiment of the present invention can be implemented. Computer system 400 includes a processor 420, such as a central processing unit, an input/output interface 430 and support circuitry 440. In certain embodiments, where the computer system 400 requires a direct human interface, a display 410 and an input device 450 such as a keyboard, mouse, pointer, motion sensor, microphone and/or camera are also provided. The display 410, input device 450, processor 420, and support circuitry 440 are shown connected to a bus 490 which also connects to a memory 460. Memory 460 includes program storage memory 470 and data storage memory 480. Note that while computer system 400 is depicted with direct human interface components display 410 and input device 450, programming of modules and exportation of data can alternatively be accomplished over the input/output interface 430, for instance, where the computer system 400 is connected to a network and the programming and display operations occur on another associated computer, or via a detachable input device as is known with respect to interfacing programmable logic controllers.

Program storage memory 470 and data storage memory 480 can each comprise volatile (RAM) and non-volatile (ROM) memory units and can also comprise hard disk and backup storage capacity, and both program storage memory 470 and data storage memory 480 can be embodied in a single memory device or separated in plural memory devices. Program storage memory 470 stores software program modules and associated data and stores one or more of: a raw data receiving module 471, having one or more software programs adapted to receive the analytic characterization data 125, for instance obtained at step 120 in the process flow diagram of FIG. 1 ; an analytical value calculation module 472, having one or more software programs adapted to determine one or more analytical values 135 based on the type of analytic characterization data 125 received by module 471, for instance calculated at step 130 in the process flow diagram of FIG. 1 using equation (5) herein based on the GPC data; one or more assigned assay value calculation modules 473, having one or more software programs adapted to determine a plurality of assigned assay values to produce a virtual assay 195 of an oil sample, for instance using the one or more analytical values 135 calculated by module 472 and the set of constants 105 (and in certain embodiments the density 110), for instance as in step 190 in the process flow diagram of FIG. 1 (in certain embodiments using steps 140, 150, 160, 170 and 180 to calculate and assign a plurality of different elemental composition values/physical properties/indicative properties that make up the virtual assay, for each of a total oil sample, a naphtha fraction, a gas oil fraction, a vacuum gas oil fraction and a vacuum residue fraction, respectively, to produce corresponding assigned assay values for the virtual assay 195, include including assigned assay values 145 pertaining to the total oil sample, assigned assay values 155 pertaining to a naphtha fraction, assigned assay values 165 pertaining to a gas oil fraction, assigned assay values 175 pertaining to a vacuum gas oil fraction and assigned assay values 185 pertaining to a vacuum residue fraction); and optionally a density receiving module 474 (in embodiments in which density is used to determine assigned assay values for the virtual assay), shown in dashed lines, having one or more software programs adapted to receive the density data 110, which in certain embodiments can be integrated in the raw data receiving module 471 or the assigned assay value calculation modules 473 (shown by overlapping dashed lines). Data storage memory 480 stores results and other data generated by the one or more program modules of the present invention, including the constants 105, the density 110, the analytic characterization data 125, the one or more analytical values 135, and the assigned assay values (which can be a single set of assigned data values to produce the virtual assay 195, or alternatively delineated by type including the assigned assay values 145, 155, 165, 175 and 185 described herein).

It is to be appreciated that the computer system 400 can be any computer such as a personal computer, minicomputer, workstation, mainframe, a dedicated controller such as a programmable logic controller, or a combination thereof. While the computer system 400 is shown, for illustration purposes, as a single computer unit, the system can comprise a group of computers which can be scaled depending on the processing load and database size.

Computer system 400 generally supports an operating system, for example stored in program storage memory 470 and executed by the processor 420 from volatile memory. According to an embodiment of the invention, the operating system contains instructions for interfacing computer system 400 to the Internet and/or to private networks.

Note that steps 110 and 120 can be carried out separate from or within the computer system 400. For example, step 110 can be carried out and the data entered into the computer system 400, for example via data storage memory 480, or as a single value incorporated in the program storage memory 470 for one or more of the modules. Step 120 can be carried out and the analytic characterization data entered into the computer system 400, for example via data storage memory 480, represented as the analytic characterization data 125.

In alternate embodiments, the present invention can be implemented as a computer program product for use with a computerized computing system. Those skilled in the art will readily appreciate that programs defining the functions of the present invention can be written in any appropriate programming language and delivered to a computer in any form, including but not limited to: (a) information permanently stored on non-writeable storage media (e.g., read-only memory devices such as ROMs or CD-ROM disks); (b) information alterably stored on writeable storage media (e.g., floppy disks and hard drives); and/or (c) information conveyed to a computer through communication media, such as a local area network, a telephone network, or a public network such as the Internet. When carrying computer readable instructions that implement the present invention methods, such computer readable media represent alternate embodiments of the present invention.

As generally illustrated herein, the system embodiments can incorporate a variety of computer readable media that comprise a computer usable medium having computer readable code means embodied therein. One skilled in the art will recognize that the software associated with the various processes described can be embodied in a wide variety of computer accessible media from which the software is loaded and activated. Pursuant to In re Beauregard, 35 U.S.P.Q.2d 1383 (U.S. Pat. No. 5,710,578), the present invention contemplates and includes this type of computer readable media within the scope of the invention. In certain embodiments, pursuant to In re Nuuten, 500 F.3d 1346 (Fed. Cir. 2007) (U.S. patent application Ser. No. 09/211,928), the scope of the present claims is limited to computer readable media, wherein the media is both tangible and non-transitory.

It is to be understood that like numerals in the drawings represent like elements through the several figures, and that not all components and/or steps described and illustrated with reference to the figures are required for all embodiments or arrangements. Further, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “including,” “comprising,” or “having,” “containing,” “involving,” and variations thereof herein, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should be noted that use of ordinal terms such as “first,” “second,” “third,” etc., in the claims to modify a claim element does not by itself connote any priority, precedence, or order of one claim element over another or the temporal order in which acts of a method are performed, but are used merely as labels to distinguish one claim element having a certain name from another element having a same name (but for use of the ordinal term) to distinguish the claim elements.

Notably, the figures and examples above are not meant to limit the scope of the present disclosure to a single implementation, as other implementations are possible by way of interchange of some or all the described or illustrated elements. Moreover, where certain elements of the present disclosure can be partially or fully implemented using known components, only those portions of such known components that are necessary for an understanding of the present disclosure are described, and detailed descriptions of other portions of such known components are omitted so as not to obscure the disclosure. In the present specification, an implementation showing a singular component should not necessarily be limited to other implementations including a plurality of the same component, and vice-versa, unless explicitly stated otherwise herein. Moreover, applicants do not intend for any term in the specification or claims to be ascribed an uncommon or special meaning unless explicitly set forth as such. Further, the present disclosure encompasses present and future known equivalents to the known components referred to herein by way of illustration.

The foregoing description of the specific implementations will so fully reveal the general nature of the disclosure that others can, by applying knowledge within the skill of the relevant art(s), readily modify and/or adapt for various applications such specific implementations, without undue experimentation, without departing from the general concept of the present disclosure. Such adaptations and modifications are therefore intended to be within the meaning and range of equivalents of the disclosed implementations, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance presented herein, in combination with the knowledge of one skilled in the relevant art(s). It is to be understood that dimensions discussed or shown are drawings are shown accordingly to one example and other dimensions can be used without departing from the disclosure.

The subject matter described above is provided by way of illustration only and should not be construed as limiting. Various modifications and changes can be made to the subject matter described herein without following the example embodiments and applications illustrated and described, and without departing from the true spirit and scope of the invention encompassed by the present disclosure, which is defined by the set of recitations in the following claims and by structures and functions or steps which are equivalent to these recitations.

TABLE 1 Fraction Boiling Point, ° C. Methane −161.5  Ethane −88.6 Propane −42.1 Butanes  −6.0 Light Naphtha 36-90 Mid Naphtha  90-160 Heavy Naphtha 160-205 Light gas Oil 205-260 Mid Gas Oil 260-315 Heavy gas Oil 315-370 Light Vacuum Gas Oil 370-430 Mid Vacuum Gas Oil 430-480 Heavy vacuum gas oil 480-565 Vacuum Residue 565+ 

TABLE 2 Property Property Unit Type Fraction Yield W % or V % Yield All API Gravity ° Physical All Kinematic Viscosity @ 38° C. cSt Physical Fraction boiling >250° C. Refractive Index @ 20° C. Unitless Physical Fraction boiling <400° C. Sulfur W % or ppmw Composition All Mercaptan Sulfur W % Composition Fraction boiling <250° C. Nickel ppmw Composition Fraction boiling >400° C. Vanadium ppmw Composition Fraction boiling >400° C. Nitrogen ppmw Composition All Flash Point ° C. Indicative All Cloud Point ° C. Indicative Fraction boiling >250° C. Pour Point ° C. Indicative Fraction boiling >250° C. Freezing Point ° C. Indicative Fraction boiling >250° C. Micro Carbon Residue W % Indicative Fraction boiling >300° C. Smoke Point mm Indicative Fraction boiling between 150- 250° C. Octane Number Unitless Indicative Fraction boiling <250° C. Cetane Index Unitless Indicative Fraction boiling between 150- 400° C. Aniline Point ° C. Indicative Fraction boiling <520° C.

TABLE 3 Fraction property Units K_(AD) X1_(AD) Naphtha Aromatics (Aro) W %  2.719493E+05 −9.386019E+05  Hydrogen (H) W % −3.596530E+04 1.236163E+05 Paraffins (P) W % −1.183150E+06 4.075037E+06 Sulfur (S) ppmw  8.835406E+05 0.000000E+00 Octane Number (ON) Unitless  1.798074E+06 −6.220640E+06  Gas Oil (GO) Aniline Point (AP) ° C.  4.248992E+04 −1.475307E+05  Cetane Number (CN) Unitless −7.553372E+04 2.674303E+05 Cloud Point (CP) ° C. −9.268573E+04 3.302115E+05 Nitrogen (N) ppmw −1.557684E+06 5.319946E+06 Sulfur (S) ppmw −1.310491E+07 3.739873E+07 Kinematic Viscosity @40° C. cSt −1.300856E+04 4.553510E+04 Pour Point (PP) ° C. −1.688094E+05 6.020844E+05 Vacuum Gas Oil Nitrogen (N) ppmw −4.351654E+04 0.000000E+00 (VGO) Sulfur (S) ppmw  2.058971E+06 0.000000E+00 Vacuum Residue Micro Carbon Residue W % −9.679867E+02 0.000000E+00 (VR) (MCR) Sulfur (S) ppmw  1.088787E+07 0.000000E+00 Oil Sample C5-Asphaltenes (C5A) W %  1.021201E+04 −3.550368E+04  Micro Carbon Resid (MCR) W %  2.155410E+03 −8.104033E+03  Pour Point (PP) ° C. −9.124373E+05 3.236310E+06 Kinematic Viscosity cSt −1.830075E+05 6.369600E+05 @100° C. Kinematic Viscosity @70° C. cSt −6.358754E+05 2.208791E+06 Nitrogen (N) ppmw −2.828952E+07 9.818353E+07 Sulfur (S) ppmw  1.310798E+08 −4.772196E+08  Total Acid Number (TAN) mg KOH/100 g  6.623230E+03 −2.350583E+04  Aromatics (Aro) W % −2.801904E+05 9.773422E+05 Fraction property Units X2_(AD) X3_(AD) Naphtha Aromatics (Aro) W %  1.086738E+06 −4.197948E+05  Hydrogen (H) W % −1.425792E+05 5.472674E+04 Paraffins (P) W % −4.672261E+06 1.780428E+06 Sulfur (S) ppmw  7.606557E+05 0.000000E+00 Octane Number (ON) Unitless  7.126552E+06 −2.716015E+06  Gas Oil (GO) Aniline Point (AP) ° C.  1.691805E+05 −6.502274E+04  Cetane Number (CN) Unitless −2.938596E+05 1.055132E+05 Cloud Point (CP) ° C. −3.701654E+05 1.379935E+05 Nitrogen (N) ppmw −5.905209E+06 2.151733E+06 Sulfur (S) ppmw −3.172710E+07 6.448891E+06 Kinematic Viscosity @40° C. cSt −5.155527E+04 1.941308E+04 Pour Point (PP) ° C. −6.772117E+05 2.532420E+05 Vacuum Gas Oil Nitrogen (N) ppmw −4.216837E+04 0.000000E+00 (VGO) Sulfur (S) ppmw  5.150074E+06 0.000000E+00 Vacuum Residue Micro Carbon Residue W %  2.090908E+03 0.000000E+00 (VR) (MCR) Sulfur (S) ppmw  1.358967E+07 0.000000E+00 Oil Sample C5-Asphaltenes (C5A) W %  3.990972E+04 −1.487203E+04  Micro Carbon Resid (MCR) W %  1.096564E+04 −5.077889E+03  Pour Point (PP) ° C. −3.702285E+06 1.416514E+06 Kinematic Viscosity cSt −7.459705E+05 2.918511E+05 @100° C. Kinematic Viscosity @70° C. cSt −2.565930E+06 9.944180E+05 Nitrogen (N) ppmw −1.123553E+08 4.293709E+07 Sulfur (S) ppmw  5.581510E+08 −2.192408E+08  Total Acid Number (TAN) mg KOH/100 g  2.652865E+04 −9.989665E+03  Aromatics (Aro) W % −1.088463E+06 4.015694E+05 Fraction property Units X4_(AD) X5_(AD) Naphtha Aromatics (Aro) W % −4.364175E+02 2.688432E+01 Hydrogen (H) W %  6.193766E+01 −5.770277E+00  Paraffins (P) W % −3.782001E+02 −3.457372E+01  Sulfur (S) ppmw −2.555227E+05 2.860091E+04 Octane Number (ON) Unitless  2.839544E+03 −1.541608E+02  Gas Oil (GO) Aniline Point (AP) ° C.  1.018883E+02 −1.278641E+01  Cetane Number (CN) Unitless −1.342322E+03 8.259788E+01 Cloud Point (CP) ° C. −1.309841E+03 1.001669E+02 Nitrogen (N) ppmw −9.499959E+03 3.781383E+02 Sulfur (S) ppmw −1.807065E+05 −4.139131E+03  Kinematic Viscosity @40° C. cSt −9.337925E+01 6.992590E+00 Pour Point (PP) ° C. −2.303533E+03 1.748609E+02 Vacuum Gas Oil Nitrogen (N) ppmw  1.447103E+04 −1.754840E+03  (VGO) Sulfur (S) ppmw −8.350723E+05 1.229521E+05 Vacuum Residue Micro Carbon Residue W %  1.725802E+02 4.654891E+00 (VR) (MCR) Sulfur (S) ppmw −3.457857E+06 4.179251E+05 Oil Sample C5-Asphaltenes (C5A) W %  7.281491E+01 −4.856764E+00  Micro Carbon Resid (MCR) W % −7.041421E+01 1.886224E+00 Pour Point (PP) ° C. −7.212191E+03 6.303136E+02 Kinematic Viscosity cSt  4.226789E+02 −2.356397E+01  @100° C. Kinematic Viscosity @70° C. cSt  5.202411E+02 −2.872027E+01  Nitrogen (N) ppmw −7.216202E+04 6.935776E+03 Sulfur (S) ppmw  1.095288E+06 −1.105379E+05  Total Acid Number (TAN) mg KOH/100 g  7.607929E+01 −6.185738E+00  Aromatics (Aro) W % −2.909267E+03 1.989955E+02 Fraction property Units X6_(AD) X7_(AD) Naphtha Aromatics (Aro) W % −6.950498E−01 1.046361E+02 Hydrogen (H) W %  1.488595E−01 1.390307E+01 Paraffins (P) W %  8.463286E−01 9.595286E+02 Sulfur (S) ppmw −7.632567E+02 −1.141645E+05  Octane Number (ON) Unitless  4.024208E+00 −1.003018E+03  Gas Oil (GO) Aniline Point (AP) ° C.  3.234727E−01 7.209083E+01 Cetane Number (CN) Unitless −2.242886E+00 3.787160E+02 Cloud Point (CP) ° C. −2.633061E+00 5.185730E+01 Nitrogen (N) ppmw −1.049745E+01 5.731881E+03 Sulfur (S) ppmw  6.416938E+01 2.874008E+05 Kinematic Viscosity @40° C. cSt −1.840074E−01 6.320883E+00 Pour Point (PP) ° C. −4.612347E+00 1.179689E+02 Vacuum Gas Oil Nitrogen (N) ppmw  5.062998E+01 6.470025E+03 (VGO) Sulfur (S) ppmw −3.384223E+03 −7.435992E+05  Vacuum Residue Micro Carbon Residue W % −3.338567E−02 −3.142466E+02  (VR) (MCR) Sulfur (S) ppmw −1.123807E+04 −1.953198E+06  Oil Sample C5-Asphaltenes (C5A) W %  1.254003E−01 −1.224109E+01  Micro Carbon Resid (MCR) W % −6.583046E−02 6.045871E+01 Pour Point (PP) ° C. −1.646790E+01 −9.069212E+02  Kinematic Viscosity cSt  6.027695E−01 −1.357684E+02  @100° C. Kinematic Viscosity @70° C. cSt  7.349485E−01 −1.729894E+02  Nitrogen (N) ppmw −1.836896E+02 −1.695038E+04  Sulfur (S) ppmw  2.828132E+03 3.756727E+05 Total Acid Number (TAN) mg KOH/100 g  1.630815E−01 2.098829E+00 Aromatics (Aro) W % −5.205782E+00 4.395462E+02

TABLE 4A RT (min) Intensity (a.u.) 16 167.7 17 799.3 18 3304.0 19 4808.9 20 6921.1 21 11001.3 22 15268.3 23 18629.2 24 18995.1 25 17286.0 26 12536.1 27 8744.1 28 5536.6 29 5722.2 30 5630.2 31 1748.0 32 1928.1 33 971.9 34 745.8 35 628.1 36 568.4 37 552.1 38 540.9 39 529.3 40 519.5 41 496.5 42 509.2 43 2403.6 44 15209.8 45 49662.1

TABLE 4B RT(min) Intensity(au) RT(min) Intensity(au) RT(min) Intensity(au) RT(min) Intensity(au) 22.003 15281.00 22.270 16338.91 22.536 17347.53 22.803 18185.64 22.011 15308.48 22.277 16367.96 22.543 17373.16 22.810 18204.07 22.018 15336.02 22.284 16397.02 22.551 17398.67 22.817 18222.11 22.025 15363.56 22.291 16426.02 22.558 17423.96 22.824 18239.99 22.032 15391.26 22.299 16454.91 22.565 17449.14 22.831 18257.58 22.039 15419.03 22.306 16483.79 22.572 17474.15 22.839 18275.00 22.047 15446.90 22.313 16512.51 22.579 17499.05 22.846 18292.31 22.054 15474.89 22.320 16541.00 22.587 17524.00 22.853 18309.45 22.061 15502.93 22.327 16569.27 22.594 17548.78 22.860 18326.53 22.068 15531.09 22.335 16597.37 22.601 17573.57 22.867 18343.45 22.075 15559.19 22.342 16625.25 22.608 17598.29 22.875 18360.25 22.083 15587.35 22.349 16652.95 22.615 17623.02 22.882 18376.89 22.090 15615.50 22.356 16680.44 22.623 17647.47 22.889 18393.41 22.097 15643.71 22.363 16707.75 22.630 17671.75 22.896 18409.71 22.104 15671.98 22.371 16734.84 22.637 17695.86 22.903 18425.84 22.111 15700.36 22.378 16761.93 22.644 17719.63 22.911 18441.80 22.119 15728.86 22.385 16788.85 22.651 17743.07 22.918 18457.54 22.126 15757.46 22.392 16815.71 22.659 17766.16 22.925 18473.16 22.133 15786.18 22.399 16842.52 22.666 17788.98 22.932 18488.67 22.140 15815.01 22.407 16869.32 22.673 17811.52 22.939 18504.01 22.147 15843.90 22.414 16896.08 22.680 17833.72 22.947 18519.36 22.155 15872.95 22.421 16922.94 22.687 17855.75 22.954 18534.59 22.162 15902.07 22.428 16949.75 22.695 17877.55 22.961 18549.70 22.169 15931.18 22.435 16976.61 22.702 17899.19 22.968 18564.77 22.176 15960.40 22.443 17003.47 22.709 17920.66 22.975 18579.60 22.183 15989.68 22.450 17030.34 22.716 17942.13 22.983 18594.38 22.191 16018.96 22.457 17057.20 22.723 17963.43 22.990 18608.88 22.198 16048.24 22.464 17084.01 22.731 17984.67 22.997 18623.21 22.205 16077.52 22.471 17110.76 22.738 18005.80 23.004 18637.26 22.212 16106.80 22.479 17137.40 22.745 18026.76 23.011 18650.98 22.219 16135.91 22.486 17163.98 22.752 18047.50 23.019 18664.30 22.227 16165.03 22.493 17190.51 22.759 18068.13 23.026 18677.39 22.234 16194.08 22.500 17216.92 22.767 18088.53 23.033 18690.20 22.241 16223.08 22.507 17243.28 22.774 18108.59 23.040 18702.74 22.248 16252.02 22.515 17269.52 22.781 18128.37 23.047 18714.99 22.255 16280.97 22.522 17295.66 22.788 18147.82 23.055 18727.02 22.263 16309.97 22.529 17321.68 22.795 18166.87 23.062 18738.99 23.069 18750.79 23.335 19053.99 23.602 19143.74 23.868 19041.17 23.076 18762.59 23.343 19059.04 23.609 19142.22 23.875 19037.69 23.083 18774.22 23.350 19064.10 23.616 19140.65 23.883 19034.20 23.091 18785.86 23.357 19069.05 23.623 19138.96 23.890 19030.66 23.098 18797.27 23.364 19073.94 23.631 19137.22 23.897 19027.07 23.105 18808.56 23.371 19078.77 23.638 19135.42 23.904 19023.53 23.112 18819.69 23.379 19083.55 23.645 19133.57 23.911 19019.99 23.119 18830.48 23.386 19088.27 23.652 19131.66 23.919 19016.61 23.127 18840.93 23.393 19092.93 23.659 19129.63 23.926 19013.35 23.134 18851.10 23.400 19097.43 23.667 19127.55 23.933 19010.21 23.141 18861.00 23.407 19101.93 23.674 19125.42 23.940 19007.28 23.148 18870.55 23.415 19106.20 23.681 19123.17 23.947 19004.64 23.155 18879.88 23.422 19110.36 23.688 19120.92 23.955 19002.34 23.163 18888.93 23.429 19114.46 23.695 19118.62 23.962 19000.26 23.170 18897.81 23.436 19118.28 23.703 19116.14 23.969 18998.52 23.177 18906.46 23.443 19121.99 23.710 19113.67 23.976 18997.17 23.184 18914.89 23.451 19125.42 23.717 19111.03 23.983 18996.10 23.191 18923.21 23.458 19128.68 23.724 19108.28 23.991 18995.43 23.199 18931.36 23.465 19131.71 23.731 19105.47 23.998 18995.09 23.206 18939.23 23.472 19134.52 23.739 19102.43 24.005 18995.09 23.213 18946.93 23.479 19137.16 23.746 19099.34 24.012 18995.43 23.220 18954.51 23.487 19139.58 23.753 19096.19 24.019 18996.04 23.227 18961.88 23.494 19141.77 23.760 19092.88 24.027 18997.00 23.235 18969.12 23.501 19143.74 23.767 19089.51 24.034 18998.29 23.242 18976.26 23.508 19145.37 23.775 19086.13 24.041 18999.81 23.249 18983.23 23.515 19146.83 23.782 19082.71 24.048 19001.66 23.256 18990.03 23.523 19147.95 23.789 19079.22 24.055 19003.80 23.263 18996.66 23.530 19148.85 23.796 19075.74 24.063 19006.22 23.271 19003.18 23.537 19149.47 23.803 19072.25 24.070 19008.97 23.278 19009.42 23.544 19149.75 23.811 19068.77 24.077 19011.89 23.285 19015.49 23.551 19149.81 23.818 19065.28 24.084 19015.10 23.292 19021.45 23.559 19149.58 23.825 19061.74 24.091 19018.52 23.299 19027.18 23.566 19149.08 23.832 19058.31 24.099 19022.23 23.307 19032.80 23.573 19148.40 23.839 19054.83 24.106 19026.00 23.314 19038.25 23.580 19147.50 23.847 19051.46 24.113 19029.99 23.321 19043.59 23.587 19146.44 23.854 19048.03 24.120 19033.98 23.328 19048.87 23.595 19145.20 23.861 19044.60 24.127 19037.97 24.135 19041.90 24.401 18860.43 24.667 18323.56 24.934 17554.40 24.142 19045.67 24.408 18849.53 24.675 18307.88 24.941 17528.04 24.149 19049.15 24.415 18838.46 24.682 18292.42 24.948 17500.96 24.156 19052.24 24.423 18827.28 24.689 18276.97 24.955 17473.14 24.163 19054.83 24.430 18815.98 24.696 18261.45 24.963 17444.64 24.171 19056.91 24.437 18804.52 24.703 18245.89 24.970 17415.42 24.178 19058.31 24.444 18792.99 24.711 18229.93 24.977 17385.52 24.185 19059.04 24.451 18781.36 24.718 18213.63 24.984 17355.00 24.192 19059.10 24.459 18769.67 24.725 18196.77 24.991 17323.98 24.199 19058.48 24.466 18757.93 24.732 18179.35 24.999 17292.34 24.207 19057.13 24.473 18746.01 24.739 18161.19 25.006 17260.42 24.214 19055.17 24.480 18734.04 24.747 18142.42 25.013 17228.11 24.221 19052.53 24.487 18721.79 24.754 18122.87 25.020 17195.62 24.228 19049.15 24.495 18709.37 24.761 18102.63 25.027 17162.97 24.235 19045.28 24.502 18696.61 24.768 18081.84 25.035 17130.32 24.243 19040.84 24.509 18683.52 24.775 18060.43 25.042 17097.66 24.250 19035.78 24.516 18670.03 24.783 18038.62 25.049 17065.13 24.257 19030.16 24.523 18656.20 24.790 18016.42 25.056 17032.70 24.264 19024.20 24.531 18641.98 24.797 17994.00 25.063 17000.55 24.271 19017.85 24.538 18627.20 24.804 17971.46 25.071 16968.46 24.279 19011.11 24.545 18612.03 24.811 17948.81 25.078 16936.65 24.286 19004.19 24.552 18596.41 24.819 17926.17 25.085 16905.01 24.293 18996.94 24.559 18580.28 24.826 17903.52 25.092 16873.43 24.300 18989.58 24.567 18563.75 24.833 17880.92 25.099 16841.79 24.307 18981.99 24.574 18546.73 24.840 17858.33 25.107 16810.03 24.315 18974.24 24.581 18529.42 24.847 17835.85 25.114 16778.00 24.322 18966.20 24.588 18511.83 24.855 17813.37 25.121 16745.57 24.329 18957.88 24.595 18494.01 24.862 17790.95 25.128 16712.53 24.336 18949.34 24.603 18476.08 24.869 17768.52 25.135 16678.81 24.343 18940.52 24.610 18458.21 24.876 17745.93 25.143 16644.41 24.351 18931.30 24.617 18440.45 24.883 17723.34 25.150 16609.17 24.358 18921.86 24.624 18422.92 24.891 17700.41 25.157 16573.09 24.365 18912.19 24.631 18405.61 24.898 17677.20 25.164 16536.11 24.372 18902.25 24.639 18388.64 24.905 17653.71 25.171 16498.46 24.379 18892.07 24.646 18371.89 24.912 17629.71 25.179 16460.02 24.387 18881.73 24.653 18355.48 24.919 17605.21 25.186 16421.07 24.394 18871.17 24.660 18339.35 24.927 17580.09 25.193 16381.56 25.200 16341.77 25.467 15089.13 25.733 13914.44 25.999 12539.79 25.207 16301.76 25.474 15051.25 25.740 13871.56 26.007 12498.31 25.215 16261.75 25.481 15013.71 25.747 13828.79 26.014 12456.73 25.222 16221.90 25.488 14976.73 25.755 13786.19 26.021 12415.14 25.229 16182.39 25.495 14940.54 25.762 13743.99 26.028 12373.72 25.236 16143.39 25.503 14905.36 25.769 13702.29 26.035 12332.52 25.243 16105.00 25.510 14871.25 25.776 13661.20 26.043 12291.67 25.251 16067.46 25.517 14838.37 25.783 13620.85 26.050 12251.20 25.258 16030.82 25.524 14806.90 25.791 13581.34 26.057 12211.30 25.265 15995.08 25.531 14776.66 25.798 13542.57 26.064 12172.02 25.272 15960.35 25.539 14747.89 25.805 13504.74 26.071 12133.35 25.279 15926.57 25.546 14720.35 25.812 13467.76 26.079 12095.42 25.287 15893.80 25.553 14693.88 25.819 13431.68 26.086 12058.21 25.294 15861.94 25.560 14668.53 25.827 13396.45 26.093 12021.85 25.301 15830.92 25.567 14643.97 25.834 13361.94 26.100 11986.22 25.308 15800.63 25.575 14620.09 25.841 13328.11 26.107 11951.32 25.315 15771.01 25.582 14596.60 25.848 13294.89 26.115 11917.21 25.323 15741.95 25.589 14573.33 25.855 13262.07 26.122 11883.88 25.330 15713.29 25.596 14550.06 25.863 13229.59 26.129 11851.17 25.337 15685.02 25.603 14526.51 25.870 13197.33 26.136 11819.14 25.344 15656.81 25.611 14502.52 25.877 13165.13 26.143 11787.72 25.351 15628.54 25.618 14477.85 25.884 13132.70 26.151 11756.75 25.359 15600.10 25.625 14452.22 25.891 13100.16 26.158 11726.29 25.366 15571.22 25.632 14425.47 25.899 13067.17 26.165 11696.23 25.373 15541.71 25.639 14397.48 25.906 13033.67 26.172 11666.50 25.380 15511.59 25.647 14368.09 25.913 12999.67 26.179 11637.10 25.387 15480.68 25.654 14337.23 25.920 12965.00 26.187 11607.82 25.395 15448.81 25.661 14304.92 25.927 12929.59 26.194 11578.71 25.402 15416.10 25.668 14271.09 25.935 12893.51 26.201 11549.66 25.409 15382.55 25.675 14235.85 25.942 12856.76 26.208 11520.60 25.416 15348.05 25.683 14199.26 25.949 12819.22 26.215 11491.55 25.423 15312.75 25.690 14161.38 25.956 12781.06 26.223 11462.43 25.431 15276.78 25.697 14122.27 25.963 12742.16 26.230 11433.21 25.438 15240.09 25.704 14082.14 25.971 12702.66 26.237 11403.93 25.445 15202.83 25.711 14041.12 25.978 12662.59 26.244 11374.48 25.452 15165.17 25.719 13999.42 25.985 12622.01 26.251 11344.86 25.459 15127.18 25.726 13957.10 25.992 12581.04 26.259 11315.19 26.266 11285.29 26.532 10235.81 26.799 8979.18 27.065 8576.45 26.273 11255.17 26.539 10214.96 26.806 8945.85 27.072 8541.78 26.280 11224.88 26.547 10194.06 26.813 8914.72 27.079 8503.90 26.287 11194.36 26.554 10172.87 26.820 8886.00 27.087 8463.04 26.295 11163.51 26.561 10151.40 26.827 8859.64 27.094 8419.32 26.302 11132.43 26.568 10129.54 26.835 8835.87 27.101 8372.90 26.309 11101.18 26.575 10107.06 26.842 8814.63 27.108 8324.17 26.316 11069.71 26.583 10083.96 26.849 8795.91 27.115 8273.48 26.323 11038.07 26.590 10059.96 26.856 8779.73 27.123 8221.04 26.331 11006.37 26.597 10035.12 26.863 8766.07 27.130 8167.26 26.338 10974.62 26.604 10009.33 26.871 8754.77 27.137 8112.58 26.345 10942.87 26.611 9982.46 26.878 8745.84 27.144 8057.50 26.352 10911.06 26.619 9954.42 26.885 8738.98 27.151 8002.43 26.359 10879.36 26.626 9925.20 26.892 8734.21 27.159 7947.86 26.367 10847.66 26.633 9894.68 26.899 8731.23 27.166 7894.07 26.374 10816.19 26.640 9862.81 26.907 8729.99 27.173 7841.58 26.381 10784.89 26.647 9829.66 26.914 8730.22 27.180 7790.83 26.388 10753.87 26.655 9795.09 26.921 8731.56 27.187 7742.22 26.395 10723.12 26.662 9759.24 26.928 8733.87 27.195 7696.14 26.403 10692.78 26.669 9722.15 26.935 8736.85 27.202 7652.86 26.410 10662.82 26.676 9683.76 26.943 8740.16 27.209 7612.73 26.417 10633.20 26.683 9644.20 26.950 8743.59 27.216 7576.15 26.424 10604.09 26.691 9603.51 26.957 8746.74 27.223 7543.27 26.431 10575.32 26.698 9561.92 26.964 8749.38 27.231 7514.27 26.439 10546.94 26.705 9519.49 26.971 8751.18 27.238 7489.43 26.446 10519.12 26.712 9476.38 26.979 8751.85 27.245 7468.81 26.453 10491.80 26.719 9432.77 26.986 8751.07 27.252 7452.34 26.460 10465.11 26.727 9388.82 26.993 8748.54 27.259 7440.09 26.467 10439.20 26.734 9344.82 27.000 8743.98 27.267 7432.00 26.475 10414.02 26.741 9300.87 27.007 8737.18 27.274 7428.01 26.482 10389.63 26.748 9257.32 27.015 8727.86 27.281 7427.89 26.489 10366.03 26.755 9214.27 27.022 8715.72 27.288 7431.43 26.496 10343.16 26.763 9171.95 27.029 8700.65 27.295 7438.29 26.503 10320.84 26.770 9130.64 27.036 8682.39 27.303 7448.35 26.511 10299.15 26.777 9090.46 27.043 8660.86 27.310 7461.05 26.518 10277.79 26.784 9051.62 27.051 8636.08 27.317 7476.06 26.525 10256.78 26.791 9014.53 27.058 8607.98 27.324 7492.86 27.331 7510.96 27.598 6158.45 27.864 5807.20 28.131 4377.47 27.339 7529.95 27.605 6063.92 27.871 5830.13 28.138 4323.35 27.346 7549.28 27.612 5971.53 27.879 5848.95 28.145 4273.50 27.353 7568.56 27.619 5881.83 27.886 5863.79 28.152 4228.54 27.360 7587.16 27.627 5795.62 27.893 5874.30 28.159 4188.75 27.367 7604.81 27.634 5713.46 27.900 5880.54 28.167 4154.69 27.375 7621.00 27.641 5636.07 27.907 5882.39 28.174 4126.59 27.382 7635.33 27.648 5563.80 27.915 5879.92 28.181 4104.67 27.389 7647.35 27.655 5497.25 27.922 5873.06 28.188 4089.05 27.396 7656.68 27.663 5436.78 27.929 5861.82 28.195 4079.83 27.403 7663.03 27.670 5382.72 27.936 5846.31 28.203 4077.02 27.411 7666.07 27.677 5335.29 27.943 5826.53 28.210 4080.51 27.418 7665.28 27.684 5294.77 27.951 5802.65 28.217 4090.29 27.425 7660.39 27.691 5261.21 27.958 5774.60 28.224 4106.19 27.432 7651.18 27.699 5234.80 27.965 5742.68 28.231 4127.89 27.439 7637.29 27.706 5215.41 27.972 5706.99 28.239 4155.20 27.447 7618.41 27.713 5202.99 27.979 5667.71 28.246 4187.74 27.454 7594.53 27.720 5197.37 27.987 5624.94 28.253 4225.11 27.461 7565.30 27.727 5198.50 27.994 5578.91 28.260 4266.76 27.468 7530.74 27.735 5205.97 28.001 5529.74 28.267 4312.16 27.475 7490.72 27.742 5219.35 28.008 5477.70 28.275 4360.72 27.483 7445.26 27.749 5238.23 28.015 5422.79 28.282 4411.86 27.490 7394.57 27.756 5262.23 28.023 5365.24 28.289 4464.86 27.497 7338.53 27.763 5290.55 28.030 5305.16 28.296 4519.15 27.504 7277.39 27.771 5322.70 28.037 5242.61 28.303 4574.06 27.511 7211.41 27.778 5358.10 28.044 5177.98 28.311 4629.02 27.519 7140.82 27.785 5396.04 28.051 5111.50 28.318 4683.42 27.526 7065.80 27.792 5435.88 28.059 5043.44 28.325 4736.70 27.533 6986.67 27.799 5477.13 28.066 4974.26 28.332 4788.29 27.540 6903.72 27.807 5519.00 28.073 4904.29 28.339 4837.80 27.547 6817.39 27.814 5560.99 28.080 4834.09 28.347 4884.56 27.555 6728.09 27.821 5602.29 28.087 4764.13 28.354 4928.29 27.562 6636.20 27.828 5642.53 28.095 4694.94 28.361 4968.58 27.569 6542.29 27.835 5680.97 28.102 4626.94 28.368 5005.17 27.576 6446.87 27.843 5717.05 28.109 4560.68 28.375 5037.65 27.583 6350.65 27.850 5750.38 28.116 4496.73 28.383 5065.92 27.591 6254.27 27.857 5780.56 28.123 4435.47 28.390 5089.75 28.397 5109.08 28.663 4514.15 28.930 5706.60 28.404 5123.86 28.671 4537.64 28.937 5710.70 28.411 5133.92 28.678 4564.90 28.944 5713.74 28.419 5139.49 28.685 4595.75 28.951 5715.98 28.426 5140.44 28.692 4629.98 28.959 5717.56 28.433 5136.96 28.699 4667.18 28.966 5718.68 28.440 5129.03 28.707 4707.14 28.973 5719.47 28.447 5116.95 28.714 4749.57 28.980 5720.20 28.455 5100.71 28.721 4793.97 28.987 5720.82 28.462 5080.59 28.728 4840.05 28.995 5721.55 28.469 5056.87 28.735 4887.37 28.476 5029.95 28.743 4935.65 28.483 5000.17 28.750 4984.37 28.491 4968.02 28.757 5033.27 28.498 4933.85 28.764 5081.88 28.505 4898.16 28.771 5129.87 28.512 4861.46 28.779 5177.03 28.519 4824.15 28.786 5223.00 28.527 4786.72 28.793 5267.45 28.534 4749.40 28.800 5310.22 28.541 4712.81 28.807 5351.13 28.548 4677.24 28.815 5389.97 28.555 4643.13 28.822 5426.67 28.563 4610.87 28.829 5461.01 28.570 4580.80 28.836 5492.98 28.577 4553.32 28.843 5522.54 28.584 4528.87 28.851 5549.69 28.591 4507.74 28.858 5574.42 28.599 4490.09 28.865 5596.78 28.606 4476.27 28.872 5616.90 28.613 4466.38 28.879 5634.72 28.620 4460.53 28.887 5650.57 28.627 4458.90 28.894 5664.34 28.635 4461.49 28.901 5676.20 28.642 4468.34 28.908 5686.20 28.649 4479.42 28.915 5694.52 28.656 4494.76 28.923 5701.20

TABLE 5 Conventional Calculated Crude Oil AD Value AD Description Unit Assay Value (Equation (4) Naphtha, Aro W % 11.0 10.9 Naphtha, H W % 14.7 14.7 Naphtha, P W % 75.8 74.1 Naphtha, S ppmw 876 876 Naphtha, ON Unitless 52.5 53.4 GO, AP ° C. 66.0 65.2 GO, CN Unitless 59.5 57.9 GO, CP ° C. −10.0 −9.9 GO, N ppmw 71.2 114.2 GO, S ppmw 13,090 12,489 GO, Kinematic Viscosity cSt 2.9 3.0 @40° C. GO, PP ° C. −9.0 −11.2 VGO, N ppmw 617 617 VGO, S ppmw 28,800 28,800 VR, MCR W % 12.4 12.4 VR, S ppmw 52,700 52,700 Oil Sample, C5A W % 1.4 1.5 Oil Sample, MCR W % 6.2 6.4 Oil Sample, PP ° C. −15.0 −17.9 Oil Sample, Kinematic cSt 11.8 11.8 Viscosity @100° C. Oil Sample, Kinematic cSt 21.7 21.8 Viscosity @70° C. Oil Sample, N ppmw 829 934 Oil Sample, S ppmw 30,000 26,277 Oil Sample, TAN mg KOH/100 g 0.1 0.2 Oil Sample, Aro W % 20.2 21.6 

1. A method for producing a virtual assay of an oil sample, wherein the oil sample is characterized by a density, selected from the group consisting of crude oil, bitumen and shale oil, and characterized by naphtha, gas oil, vacuum gas oil and vacuum residue fractions, the method comprising: entering into a computer gel permeation chromatography (GPC) data indicative of GPC peak intensity values at predetermined GPC retention time increments between a predetermined range of GPC retention times for a solution of the oil sample without distillation in a GPC solvent; calculating and assigning, as a function of the GPC data, an analytical value (AV); and calculating and assigning, as a function of the AV and the density of the oil sample, virtual assay data of the oil sample and the naphtha, gas oil, vacuum gas oil and vacuum residue fractions, said virtual assay data comprising a plurality of assigned data values.
 2. The method of claim 1, wherein virtual assay data comprises: a plurality of assigned assay data values pertaining to the oil sample including one or more of aromatic content, C5-asphaltenes content, elemental compositions of sulfur and nitrogen, micro-carbon residue content, total acid number and viscosity; a plurality of assigned assay values pertaining to the vacuum residue fraction of the oil sample including one or more of elemental composition of sulfur and micro-carbon residue content; a plurality of assigned assay values pertaining to the vacuum gas oil fraction of the oil sample including elemental compositions of one or more of sulfur and nitrogen; a plurality of assigned assay values pertaining to the gas oil fraction of the oil sample including one or more of elemental compositions of sulfur and nitrogen, viscosity, and indicative properties including aniline point, cetane number, cloud point and pour point; and a plurality of assigned assay values pertaining to the naphtha fraction of the oil sample including one or more of aromatic content, elemental composition of hydrogen and sulfur, paraffin content and octane number.
 3. The method of claim 1, wherein virtual assay data comprises: a plurality of assigned assay data values pertaining to the oil sample including aromatic content, C5-asphaltenes content, elemental compositions of sulfur and nitrogen, micro-carbon residue content, total acid number and viscosity; a plurality of assigned assay values pertaining to the vacuum residue fraction of the oil sample including elemental composition of sulfur and micro-carbon residue content; a plurality of assigned assay values pertaining to the vacuum gas oil fraction of the oil sample including elemental compositions of sulfur and nitrogen; a plurality of assigned assay values pertaining to the gas oil fraction of the oil sample including elemental compositions of sulfur and nitrogen, viscosity, and indicative properties including aniline point, cetane number, cloud point and pour point; and a plurality of assigned assay values pertaining to the naphtha fraction of the oil sample including aromatic content, elemental composition of hydrogen and sulfur, paraffin content and octane number.
 4. The method of claim 3, wherein virtual assay data further comprises: yields of fractions from the oil sample as mass fractions of boiling point ranges, including one or more of naphtha, gas oil, vacuum gas oil and vacuum residue; composition information of hydrogen sulfide and/or mercaptans in the oil sample and/or its fractions; elemental compositions of one or more of carbon, hydrogen, nickel, and vanadium; physical properties of the oil sample and/or its fractions including one or more of API gravity and refractive index; or indicative properties of the oil sample and/or its fractions including one or more of flash point, freezing point and smoke point.
 5. The method of claim 1, further comprising analyzing the solution of the oil sample without distillation in a GPC solvent by gel permeation chromatography to obtain the GPC data.
 6. The method of claim 1, wherein each assay value is determined by a multi-variable polynomial equation with predetermined constant coefficients developed using linear regression techniques, wherein corresponding variables are the AV and the density of the oil sample.
 7. The method of claim 6, wherein each assay value is determined by AD=K _(AD) +X1_(AD)*AV+X2_(AD)*AV² +X3_(AD)*AV³ +X4_(AD)*ρ*AV where: AD is the assigned assay value that is a value and/or property representative of an elemental composition value, a physical property or an indicative property; AV is the analytical value of the oil sample; ρ is the density of the oil sample; and K_(AD), X1_(AD), X2_(AD), X3_(AD), and X4_(AD) are constants.
 8. The method of claim 6, wherein each assay value is determined by AD=K _(AD) +X1_(AD) *ρ+X2_(AD)*ρ² +X3_(AD)*ρ³ +X4_(AD)*AV+X5_(AD)*AV² +X6_(AD)*AV³ +X7_(AD)*ρ*AV where: AD is the assigned assay value that is a value and/or property representative of an elemental composition value, a physical property or an indicative property; AV is the analytical value of the oil sample; ρ is the density of the oil sample; and K_(AD), X1_(AD), X2_(AD), X3_(AD), X4_(AD), X5_(AD), X6_(AD) and X7_(AD) are constants.
 9. The method of claim 7 or 8, wherein the analytical value is a GPC index derived from a summation of GPC peak intensities obtained at plural GPC retention times over a range of GPC retention times, or a summation of GPC peak intensities multiplied by a corresponding molecular weight, over a range of molecular weights, wherein where the molecular weights are obtained as a function of the GPC retention times.
 10. The method of claim 9, wherein the GPC index (GPCI) is derived from a summation of GPC peak intensities obtained at plural GPC retention times over a range of GPC retention times and is obtained by a function ${GPCI} = {\sum\limits_{{RT} = {RT1}}^{{RT} = {RT2}}\frac{{GPC}{peak}{intensity}}{1,000,000}}$ where: GPC peak intensity=intensity value based on analysis of the oil sample (where the oil sample is in a GPC solvent as a solution) at a given GPC retention time (RT), obtained over a range of GPC retention times RT1 to RT2.
 11. The method of claim 10, wherein RT1 is in the range of about 21-23 minutes and RT2 is in the range of about 28-30 minutes, and wherein the range is divided into about 800-1100 intervals.
 12. A system for producing a virtual assay of an oil sample, wherein the oil sample is characterized by a density, selected from the group consisting of crude oil, bitumen and shale oil, and characterized by naphtha, gas oil, vacuum gas oil and vacuum residue fractions, the system comprising: a gel permeation chromatography system that outputs gel permeation chromatography system (GPC) data; a non-volatile memory device that stores calculation modules and data, the data including the GPC data, wherein the GPC data, is indicative of GPC peak intensity values at predetermined GPC retention time increments between a predetermined range of GPC retention times for a solution of the oil sample without distillation in a GPC solvent; a processor coupled to the non-volatile memory device; a first calculation module that is stored in the non-volatile memory device and that is executed by the processor, wherein the first calculation module calculates an analytical value (AV) as a function of the GPC data; and a second calculation module that is stored in the non-volatile memory device and that is executed by the processor, wherein the second calculation module calculates, as a function of the AV and the density of the oil sample, virtual assay data of the oil sample and the naphtha, gas oil, vacuum gas oil and vacuum residue fractions, said virtual assay data comprising a plurality of assigned data values.
 13. The system as in claim 12, wherein virtual assay data comprises: a plurality of assigned assay data values pertaining to the oil sample including aromatic content, C5-asphaltenes content, elemental compositions of sulfur and nitrogen, micro-carbon residue content, total acid number and viscosity; a plurality of assigned assay values pertaining to the vacuum residue fraction of the oil sample including elemental composition of sulfur and micro-carbon residue content; a plurality of assigned assay values pertaining to the vacuum gas oil fraction of the oil sample including elemental compositions of sulfur and nitrogen; a plurality of assigned assay values pertaining to the gas oil fraction of the oil sample including elemental compositions of sulfur and nitrogen, viscosity, and indicative properties including aniline point, cetane number, cloud point and pour point; a plurality of assigned assay values pertaining to the naphtha fraction of the oil sample including aromatic content, elemental composition of hydrogen and sulfur, paraffin content and octane number.
 14. The system as in claim 13, wherein virtual assay data further comprises: yields of fractions from the oil sample as mass fractions of boiling point ranges, including one or more of naphtha, gas oil, vacuum gas oil and vacuum residue; composition information of hydrogen sulfide and/or mercaptans in the oil sample and/or its fractions; elemental compositions of one or more of carbon, hydrogen, nickel, and vanadium; physical properties of the oil sample and/or its fractions including one or more of API gravity and refractive index; or indicative properties of the oil sample and/or its fractions including one or more of flash point, freezing point and smoke point.
 15. The system of claim 12, wherein each assay value is calculated and assigned by the second calculation module with a multi-variable polynomial equation with predetermined constant coefficients developed using linear regression techniques, wherein corresponding variables are the AV and the density of the oil sample.
 16. The system of claim 15, wherein each assay value is calculated and assigned by the second calculation module with a function: AD=K _(AD) +X1_(AD)*AV+X2_(AD)*AV² ±X3_(AD)*AV³ +X4_(AD)*ρ*AV where: AD is the assigned assay value that is a value and/or property representative of an elemental composition value, a physical property or an indicative property; AV is the analytical value of the oil sample; ρ is the density of the oil sample; and K_(AD), X1_(AD), X2_(AD), X3_(AD), and X4_(AD) are constants.
 17. The system of claim 15, wherein each assay value is calculated and assigned by the second calculation module with a function: AD=K _(AD) +X1_(AD) *ρ+X2_(AD)*ρ² +X3_(AD)*ρ³ +X4_(AD)*AV+X5_(AD)*AV² +X6_(AD)*AV³ +X7_(AD)*ρ*AV where: AD is the assigned assay value that is a value and/or property representative of an elemental composition value, a physical property or an indicative property; AV is the analytical value of the oil sample; ρ is the density of the oil sample; and K_(AD), X1_(AD), X2_(AD), X3_(AD), X4_(AD), X5_(AD), X6_(AD) and X7_(AD) are constants.
 18. The system of claim 17, wherein the analytical value is a GPC index derived from a summation of GPC peak intensities obtained at plural GPC retention times over a range of GPC retention times, or a summation of GPC peak intensities multiplied by a corresponding molecular weight, over a range of molecular weights, wherein where the molecular weights are obtained as a function of the GPC retention times.
 19. The system of claim 18, wherein the GPC index (GPCI) is derived from a summation of GPC peak intensities obtained at plural GPC retention times over a range of GPC retention times and is obtained by a function ${GPCI} = {\sum\limits_{{RT} = {RT1}}^{{RT} = {RT2}}\frac{{GPC}{peak}{intensity}}{1,000,000}}$ where: GPC peak intensity=intensity value based on analysis of the oil sample (where the oil sample is in a GPC solvent as a solution) at a given GPC retention time (RT), obtained over a range of GPC retention times RT1 to RT2.
 20. The system of claim 19, wherein RT1 is in the range of about 21-23 minutes and RT2 is in the range of about 28-30 minutes, and wherein the range is divided into about 800-1100 intervals. 